Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Nonlinear models”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, we, in this paper, propose a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Investigating the Influence of Ni, ZrO 2 , and Y 2 O 3 from SOFC Anodes on Siloxane Deposition

Siloxanes, as a type of impurity in biogas, can poison the Ni-YSZ anode of SOFCs. However, the influence of individual components of the anode, such as Ni, ZrO 2 , and Y 2 O 3 , on the siloxane deposition process has not been investigated extensively. In this study, Ni, ZrO 2 , and Y 2 O 3 pellets were exposed to H 2 + N 2 + H 2 O + D4 (octamethylcyclotetrasiloxane, 2.5 ppmv) and H 2 + N 2 + D4 (2.5 ppmv siloxane) gas mixtures at 750 °C to investigate their affinity and tolerance for siloxane degradation. Surface morphology analysis and electrochemical analysis including electrochemical impedance spectroscopy (EIS), related distribution of relaxation times (DRT) analysis and equivalent circuit modeling with complex nonlinear least square (CNLS) fitting were conducted. Here, a microstructure parameter—tortuosity factor to porosity ratio $\tau /\varepsilon $ calculated by diffusion polarization resistance was utilized for siloxane deposition evaluation. After comparing pellets surface morphology changes before and after experiments and $\tau /\varepsilon $ change following the contamination, Ni is considered as a major factor in siloxane deposition reactions in Ni-YSZ anode.

25 ENERGY STORAGE↗
DOE OSTI2024

Thermodynamics-informed latent space dynamics identification

This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

Cheung, Siu Wun↗
DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2023

Physics of the thermal quench in MST tokamak plasmas (Final Technical Report)

This project at the University of Wisconsin-Madison targeted measurements in tokamak plasmas in the Madison Symmetric Torus (MST) to help elucidate the physics of the tokamak disruption. We intended to focus on the thermal quench, during which energy is lost from the plasma in a very short time. Understanding and ultimately mitigating the thermal quench are among the highest priority research thrusts for ITER, a large international fusion experiment presently under construction. The measurements in MST exploited an advanced set of diagnostics for internal measurements with high time resolution, targeting linear and nonlinear magnetohydrodynamic (MHD) activity as well as the electron temperature and density profiles. We also exploited other features of the MST device, including very flexible power supplies for the toroidal magnetic field and toroidal plasma current that are capable of producing almost arbitrary waveforms. While the work funded by this project was purely experimental, we continued and expanded an existing collaboration with UW-Madison experts in nonlinear MHD computational modeling of tokamak plasmas. That modeling incorporated realistic, experimentally measured parameters. The results of the modeling were anticipated to deepen considerably our understanding of the experimental measurements, and in turn, the experimental measurements were anticipated to help validate the modeling results. The science of transients such as disruptions is one of the highest priority research areas in the U.S. and international fusion programs. The work carried out in this project was targeted to help advance the science of tokamak disruptions which will in turn contribute to the success of ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Technical Report on Subsurface Monitoring of the Brady Hot Spring Geothermal Site, Nevada, based upon Full Waveform Inversion

Abilities to accurately characterize the subsurface in a geothermal setting is key to assess and support production. An important element of geothermal reservoir monitoring is also the ability to investigate fluid transport within fracture network. This report focuses on improving subsurface imaging and monitoring in geothermal settings using full waveform inversion based on the adjoint method and time-lapse imaging. To assess our method, we rely on a dense seismic dataset collected in 2016 at the Brady Hot Springs geothermal site in Nevada for the DOE-funded project Poroelastic Tomography by Adjoint Inverse Modeling of Data from Seismology, Geodesy, and Hydrology. This dataset captures subsurface changes across four stages of geothermal power plant operations, which involve varying rates of fluid injection and extraction. Two velocity models were previously derived from this dataset using different methods: one based on travel times and another on sweep interferometry. Our first step is to refine these models using adjoint tomography, which has been applied successfully at global and regional-scales but is less common at the reservoir-scale. Two approaches are then explored for time-lapse analysis: directly comparing refined tomographic models from different stages or backpropagating waveform differences relative to a baseline tomographic model. The main take away is that both approaches highlight similar reservoir behaviors, but the latter approach is more computationally effective in capturing small-scale changes in subsurface properties. For this work, we leverage the use of Salvus (www.mondaic.com), an end-to-end seismic imaging solution, relying on the spectral element method to compute forward and adjoint simulations, and developed by Mondaic Ltd. It includes integrated workflow management that handles waveform and metadata, launches simulations, computes waveform misfits and adjoint sources, and iterates for model updates by nonlinear optimization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner

We report in this paper describes how the performance of motion primitive-based planning algorithms can be improved using reinforcement learning. Specifically, we describe and evaluate a framework that autonomously improves the performance of a primitive-based motion planner. The improvement process consists of three phases: exploration, extraction, and reward updates. This process can be iterated continuously to provide successive improvement. The exploration step generates new trajectories, and the extraction step identifies new primitives from these trajectories. These primitives are then used to update rewards for continued exploration. This framework required novel shaping rewards, development of a primitive extraction algorithm, and modification of the Hybrid A* algorithm. The framework is tested on a navigation task using a nonlinear F-16 model. The framework autonomously added 91 motion primitives to the primitive library and reduced average path cost by 21.6 seconds, or 35.75% of the original cost. The learned primitives are applied to an obstacle field navigation task, which was not used in training, and reduced path cost by 16.3 seconds, or 24.1%. Additionally, two heuristics for the modified Hybrid A* algorithm are designed to improve effective branching factor.

42 ENGINEERING↗
DOE OSTI2022

Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters

The ability to generate physically plausible ensembles of variable sources is critical to the optimization of time domain survey cadences and the training of classification models on data sets with few to no labels. Traditional data augmentation techniques expand training sets by reenvisioning observed exemplars, seeking to simulate observations of specific training sources under different (exogenous) conditions. Unlike fully theory-driven models, these approaches do not typically allow principled interpolation nor extrapolation. Moreover, the principal drawback of theory-driven models lies in the prohibitive computational cost of simulating source observables from ab initio parameters. In this work, we propose a computationally tractable machine learning approach to generate realistic light curves of periodic variables capable of integrating physical parameters and variability classes as inputs. Our deep generative model, inspired by the transparent latent space generative adversarial networks, uses a variational autoencoder (VAE) architecture with temporal convolutional network layers, trained using the OGLE-III optical light curves and physical characteristics (e.g., effective temperature and absolute magnitude) from Gaia DR2. A test using the temperature–shape relationship of RR Lyrae demonstrates the efficacy of our generative “physics-enhanced latent space VAE” (PELS-VAE) model. Such deep generative models, serving as nonlinear nonparametric emulators, present a novel tool for astronomers to create synthetic time series over arbitrary cadences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Detection of Cosmological 21 cm Emission with the Canadian Hydrogen Intensity Mapping Experiment

We present a detection of 21 cm emission from large-scale structure (LSS) between redshift 0.78 and 1.43 made with the Canadian Hydrogen Intensity Mapping Experiment. Radio observations acquired over 102 nights are used to construct maps that are foreground filtered and stacked on the angular and spectral locations of luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasars (QSOs) from the eBOSS clustering catalogs. We find decisive evidence for a detection when stacking on all three tracers of LSS, with the logarithm of the Bayes factor equal to 18.9 (LRG), 10.8 (ELG), and 56.3 (QSO). An alternative frequentist interpretation, based on the likelihood ratio test, yields a detection significance of 7.1σ (LRG), 5.7σ (ELG), and 11.1σ (QSO). These are the first 21 cm intensity mapping measurements made with an interferometer. We constrain the effective clustering amplitude of neutral hydrogen (H I ), defined as ${{ \mathcal A }}_{{\rm{H}}\,{\rm\small{I}}}\equiv {10}^{3}\,{{\rm{\Omega }}}_{{\rm{H}}\,{\rm\small{I}}}\left({b}_{{\rm{H}}\,{\rm\small{I}}}+\langle \,f{\mu }^{2}\rangle \right)$, where Ω H I is the cosmic abundance of H I , b H I is the linear bias of H I , and $\langle$fμ 2 $\rangle$ = 0.552 encodes the effect of redshift-space distortions at linear order. We find ${{ \mathcal A }}_{{\rm{H}}\,{\rm\small{I}}}={1.51}_{-0.97}^{+3.60}$ for LRGs (z = 0.84), ${{ \mathcal A }}_{{\rm{H}}\,{\rm\small{I}}}={6.76}_{-3.79}^{+9.04}$ for ELGs (z = 0.96), and ${{ \mathcal A }}_{{\rm{H}}\,{\rm\small{I}}}={1.68}_{-0.67}^{+1.10}$ for QSOs (z = 1.20), with constraints limited by modeling uncertainties at nonlinear scales. We are also sensitive to bias in the spectroscopic redshifts of each tracer, and we find a nonzero bias Δ v = - 66 ± 20 km s -1 for the QSOs. We split the QSO catalog into three redshift bins and have a decisive detection in each, with the upper bin at z = 1.30 producing the highest-redshift 21 cm intensity mapping measurement thus far.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1966

Theory and Practical Design of Phase-locked Receivers, Volume I

This is Volume I of a two-volume work on the theory, of phase-locked receivers, with pertinent reference material on practical receiver design. Volume I is primarily devoted to the performance of carrier-tracking loops, including a rigorous treatment of narrow-band systems having IF limiters. The bulk of the work is based on a theoretical linear model, but a nonlinear method is also presented to predict behavior near the threshold. The emphasis throughout the work is toward completeness, simplicity, and internal consistency of the material assembled. Part I of this Volume is an exposition of the theory, the resulting equations, and the design philosophy that have enabled the phase-lock concept to evolve into the basic principle underlying the most sensitive receivers il, the world today. Part II is a condensed version of Part I, intended as a quick reference to formulas, definitions, and salient design considerations.

RECEIVER↗
NASA NTRS1969

Higher order resonances in a plasma.

Plasma resonances driven into nonlinear regime, using models of cold plasma driven by wave source and unmagnetized Vlasov plasma by two grid source

Chen, C. S.↗
NASA NTRS1971

Parameter identification using a creeping-random-search algorithm

A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

Parrish, R. V.↗
NASA NTRS1973

Thermal conductivity of heterogeneous mixtures and lunar soils

The theoretical evaluation of the effective thermal conductivity of granular materials is discussed with emphasis upon the heat transport properties of lunar soil. The following types of models are compared: probabilistic, parallel isotherm, stochastic, lunar, and a model based on nonlinear heat flow system synthesis.

Vachon, R. I.↗
NASA NTRS1973

Analysis and modeling of a family of two-transistor parallel inverters

A family of five static dc-to-square-wave inverters, each employing a square-loop magnetic core in conjunction with two switching transistors, is analyzed using piecewise-linear models for the nonlinear characteristics of the transistors, diodes, and saturable-core devices. Four of the inverters are analyzed in detail for the first time. These analyses show that, by proper choice of a frame of reference, each of the five quite differently appearing inverter circuits can be described by a common equivalent circuit. This equivalent circuit consists of a five-segment nonlinear resistor, a nonlinear saturable reactor, and a linear capacitor. Thus, by proper interpretation and identification of the parameters in the different circuits, the results of a detailed solution for one of the inverter circuits provide similar information and insight into the local and global behavior of each inverter in the family.

Lee, F. C. Y.↗
NASA NTRS1975

Upwind second-order difference schemes and applications in unsteady aerodynamic flows

Explicit second-order upwind difference schemes in combination with spatially symmetric schemes can produce larger stability bounds and better numerical resolution than symmetric schemes alone. However, if conservation form is essential, a special operator is required for transition between schemes. An operational approach has been devised for deriving transition operators so that strict conservation and local consistency are maintained. Various aspects of hybrid schemes are studied numerically for model linear and nonlinear equations. To demonstrate the utility of combining two different algorithms, MacCormack's explicit, noncentered, second-order method is combined with a completely upwind version, and numerical solutions of the Euler equations are obtained for two-dimensional, transonic flows with embedded supersonic regions and shock waves. The general utility of the operational approach for combining schemes is emphasized by deriving a second-order conservative scheme for the steady transonic small-disturbance potential equation.

Warming, R. F.↗